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Guthrie, William F.; Yashchin, Emmanuel
2012 Applied Stochastic Models in Business and Industry
doi: 10.1002/asmb.918
The Poisson distribution is a popular distribution for modeling count data, yet it is constrained by its equidispersion assumption, making it less than ideal for modeling real data that often exhibit over‐dispersion or under‐dispersion. The COM‐Poisson distribution is a two‐parameter generalization of the Poisson distribution that allows for a wide range of over‐dispersion and under‐dispersion. It not only generalizes the Poisson distribution but also contains the Bernoulli and geometric distributions as special cases. This distribution's flexibility and special properties have prompted a fast growth of methodological and applied research in various fields. This paper surveys the different COM‐Poisson models that have been published thus far and their applications in areas including marketing, transportation, and biology, among others. Copyright © 2011 John Wiley & Sons, Ltd.
Guthrie, William F.; Yashchin, Emmanuel
2012 Applied Stochastic Models in Business and Industry
doi: 10.1002/asmb.900
In many quality control applications, the necessary distributional assumptions to correctly apply the traditional parametric control charts are either not met or there is simply no enough information or evidence to verify the assumptions. It is well known that the performance of many parametric control charts can be seriously degraded in situations like this. Thus, control charts that do not require a specific distributional assumption to be valid, the so‐called nonparametric or distribution‐free charts, are desirable in practice. In this paper, two simple to use multivariate nonparametric control charts are considered. The charts are Shewhart‐type charts and are based on the multivariate forms of the sign and the Wilcoxon signed‐rank tests. The performance of the proposed charts is studied in a simulation study. Some observations and recommendations are made. Copyright © 2011 John Wiley & Sons, Ltd.
Guthrie, William F.; Yashchin, Emmanuel
2012 Applied Stochastic Models in Business and Industry
doi: 10.1002/asmb.884
We present a framework for developing hierarchical models for predicting system health (e.g. probability of failure within a given mission duration), based on component‐level reliability and degradation models. Component models may be specified as parametric probability distributions or nonparametrically as empirical distribution functions. Flowgraph methods are then used to predict the system failure time distribution. We illustrate with an application to aircraft maintenance. Copyright © 2011 John Wiley & Sons, Ltd.
Guthrie, William F.; Yashchin, Emmanuel
2012 Applied Stochastic Models in Business and Industry
doi: 10.1002/asmb.947
This article proposes a method for Pareto charting that is based on unsupervised, freestyle text such as customer complaint, rework, scrap, or maintenance event descriptions. The proposed procedure is based on a slight extension of the latent Dirichlet allocation method to form multifield latent Dirichlet allocation. The extension is the usage of field‐specific dictionaries for multifield databases and changes to recommended default prior settings. We use a numerical study to motivate the prior setting selection. A real‐world case study associated with user reviews of Toyota Camry vehicles is used to illustrate the practical value of the proposed methods. The results indicate that only 4% of the words written by Consumer Reports reviewers from the last 10 years relate to the widely publicized unintended acceleration issue. Copyright © 2012 John Wiley & Sons, Ltd.
Guthrie, William F.; Yashchin, Emmanuel
2012 Applied Stochastic Models in Business and Industry
doi: 10.1002/asmb.917
We give a description of the steps leading to a robustification of a dose–response study. The original experiment was designed and described by Rosenberger and Grill (1997) and has since been discussed by several other groups of researchers. Our robustification consists of redesigning the experiment so as to build in flexibility over a range of possible link functions, including the logistic link assumed by the original experimenters. We consider as well an asymptotic Neyman–Pearson test of the validity of the assumed link function.Copyright © 2011 John Wiley & Sons, Ltd.
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